ANMAS Security System

AI-Powered Network Malicious Packet Analysis System

ANMAS combines AI models with RAG-enhanced retrieval technology to deliver advanced on-premises AI network packet analysis for enterprises. It helps identify hidden APT activity, unknown malware threats, and suspicious traffic inside internal networks.

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Product Highlights and Core Technologies

Designed for enterprise security operations, ANMAS helps automate packet-level investigation, reduce SOC workload, and provide actionable threat analysis.

Fine-Tuned AI Language Model

ANMAS uses AI models trained and fine-tuned with years of accumulated packet data from both malware behavior and normal network activity. The system performs deep AI inference locally and provides intelligent threat identification and learning capabilities.

Automated Large-Scale Packet Analysis

The system can connect directly to packet file directories or NAS devices, continuously process large volumes of daily PCAP files, and generate cybersecurity analysis reports to significantly reduce the workload of SOC engineers.

MITRE ATT&CK Mapping

ANMAS analyzes and flags potential network threat patterns such as lateral movement, hidden communication, and abnormal traffic behavior. It can also map suspicious activities to MITRE ATT&CK techniques such as T1048 and T1486, with clear response recommendations.

Optimized On-Premises Architecture

Sensitive data does not need to be uploaded to the cloud. ANMAS supports NVIDIA DGX Spark architecture and is compatible with major open-source AI frameworks, including LM Studio and Ollama, as well as enterprise-grade hardware platforms.

Security Challenges ANMAS Helps Solve

Daily security operations are time-consuming, and massive network traffic makes it difficult for traditional IDS/IPS systems to detect unknown threats. ANMAS helps identify abnormal activity hidden inside common network communication.

Threat Scenarios

  • Data exfiltration traffic generated by malware
  • Abnormal internal file access related to ransomware behavior, such as SMB access-denied anomalies
  • Suspicious network activity, including abnormal ARP scans or port scans
  • Covert communication from external APT groups already present inside enterprise networks

From Rule Matching to AI-Assisted Packet Investigation

ANMAS is built to go beyond traditional signature and rule-based detection. By combining cybersecurity forensics experience with fine-tuned AI analysis, it helps enterprises discover suspicious behavior that may otherwise remain hidden in routine network traffic.

Target Users and Deployment Architecture

ANMAS is suitable for organizations that need to analyze large volumes of packet data, accelerate security investigation, and produce professional reports aligned with recognized cybersecurity frameworks.

Who Needs ANMAS?

  • SOC service teams and network engineers handling large volumes of recorded PCAP files
  • Cybersecurity service providers performing vulnerability assessment and packet analysis for clients
  • Academic and research institutions conducting network packet analysis experiments
  • Network equipment and storage vendors seeking to add advanced cybersecurity value to hardware products

Recommended Hardware and Supported Technologies

Supported Models GPT-OSS, Gemma, Phi4, and other models compatible with the GGUF format.
Local AI Frameworks LM Studio, anything-LLM, GPT4ALL, Ollama, and other open-source frameworks.
Recommended Computing Hardware NVIDIA DGX Spark with 128GB VRAM, or a GPU system equipped with at least RTX 5090 24GB VRAM or higher, is recommended for optimal analysis performance.

Experience Next-Generation AI-Powered Packet Analysis

Protect your internal network with an AI-assisted analysis system built on years of cybersecurity forensics and packet investigation experience.

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